[目的/意义] 针对当前数字档案服务质量智能化程度不足、服务内容单一等短板，设想构建数字档案知识图谱整体架构，达到数字档案大数据的统计分析、数字档案资源集成优化以及数字档案整体服务水平提升的目的。[方法/过程] 通过收集文献分析数字档案馆的服务缺陷，体验式调研各省市数字档案馆网页服务水平，汇总各档案馆目前服务模式的不足，完善数字档案知识图谱架构流程，最终以流程图的形式展示。[结果/结论] 知识图谱能够将多种类型的数字档案文本转化为计算机可理解的数据，提高计算机智能识别水平，同时图谱所具备的动态时序性和针对性能够按照时间节点提高档案整合程度，同时基于用户浏览检索痕迹更新用户数据，提升服务质量，并增强数字档案馆之间的合作交流以达到整合资源的效果，为更好地优化数字档案服务提供有益参考。

[Purpose/significance] Aiming at shortcomings of the current service quality of digital archives, such as insufficient intelligence and single service content, this paper proposed to build an overall framework of knowledge graph of digital archives, so as to achieve statistical analysis of big data for digital archive, integration and optimization of digital archiving resources, and improvement on the overall service level of digital archives. [Method/process] By collecting literatures, service deficiencies of digital archives were analyzed. This paper investigated the web page service level of digital archives in various provinces and cities, summarized deficiencies of the current service mode of each archive, and improved the framework process of digital archives’ knowledge graph, finally the framework process was presented in the form of flow chart. [Result/conclusion] Knowledge graph can transform multiple types of digital archive text into data that computers can understand, and improve the level of computer intelligent identification. At the same time, dynamic timing and pertinence of the graph can improve the degree of integration archives according to the time node, user data can be updated based on users’ retrieval trace to improve the service quality, enhance the cooperation and communication between digital archives to achieve the result of resources integration, and provide a useful reference to better optimize the digital archiving service.